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Applied Data Science with Python and Jupyter. Use powerful industry-standard tools to unlock new, actionable insights from your data

(ebook) (audiobook) (audiobook) Książka w języku 1
Autor:
Alex Galea
Applied Data Science with Python and Jupyter. Use powerful industry-standard tools to unlock new, actionable insights from your data Alex Galea - okladka książki

Applied Data Science with Python and Jupyter. Use powerful industry-standard tools to unlock new, actionable insights from your data Alex Galea - okladka książki

Applied Data Science with Python and Jupyter. Use powerful industry-standard tools to unlock new, actionable insights from your data Alex Galea - audiobook MP3

Applied Data Science with Python and Jupyter. Use powerful industry-standard tools to unlock new, actionable insights from your data Alex Galea - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
192
Dostępne formaty:
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Ebook (29,90 zł najniższa cena z 30 dni)

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Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.

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O autorze książki

Alex Galea has been professionally practicing data analytics since graduating with a masters degree in physics from the University of Guelph, Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. Alex is currently doing web data analytics, where Python continues to play a key role in his work. He is a frequent blogger about data-centric projects that involve Python and Jupyter Notebooks.

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